EP3086093A1 - Verfahren und system zur bestimmung der struktur eines stromverteilungsnetzes, und entsprechendes computerprogramm - Google Patents
Verfahren und system zur bestimmung der struktur eines stromverteilungsnetzes, und entsprechendes computerprogramm Download PDFInfo
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- EP3086093A1 EP3086093A1 EP16166742.3A EP16166742A EP3086093A1 EP 3086093 A1 EP3086093 A1 EP 3086093A1 EP 16166742 A EP16166742 A EP 16166742A EP 3086093 A1 EP3086093 A1 EP 3086093A1
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- 238000009826 distribution Methods 0.000 title claims abstract description 31
- 230000005611 electricity Effects 0.000 title claims abstract description 27
- 238000004590 computer program Methods 0.000 title claims description 5
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- 238000005259 measurement Methods 0.000 claims description 19
- 238000004422 calculation algorithm Methods 0.000 claims description 17
- 238000005457 optimization Methods 0.000 claims description 17
- 238000004364 calculation method Methods 0.000 claims description 14
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- H—ELECTRICITY
- H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
- H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
- H02J3/00—Circuit arrangements for ac mains or ac distribution networks
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01R—MEASURING ELECTRIC VARIABLES; MEASURING MAGNETIC VARIABLES
- G01R19/00—Arrangements for measuring currents or voltages or for indicating presence or sign thereof
- G01R19/25—Arrangements for measuring currents or voltages or for indicating presence or sign thereof using digital measurement techniques
- G01R19/2513—Arrangements for monitoring electric power systems, e.g. power lines or loads; Logging
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- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y04—INFORMATION OR COMMUNICATION TECHNOLOGIES HAVING AN IMPACT ON OTHER TECHNOLOGY AREAS
- Y04S—SYSTEMS INTEGRATING TECHNOLOGIES RELATED TO POWER NETWORK OPERATION, COMMUNICATION OR INFORMATION TECHNOLOGIES FOR IMPROVING THE ELECTRICAL POWER GENERATION, TRANSMISSION, DISTRIBUTION, MANAGEMENT OR USAGE, i.e. SMART GRIDS
- Y04S20/00—Management or operation of end-user stationary applications or the last stages of power distribution; Controlling, monitoring or operating thereof
- Y04S20/30—Smart metering, e.g. specially adapted for remote reading
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- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y04—INFORMATION OR COMMUNICATION TECHNOLOGIES HAVING AN IMPACT ON OTHER TECHNOLOGY AREAS
- Y04S—SYSTEMS INTEGRATING TECHNOLOGIES RELATED TO POWER NETWORK OPERATION, COMMUNICATION OR INFORMATION TECHNOLOGIES FOR IMPROVING THE ELECTRICAL POWER GENERATION, TRANSMISSION, DISTRIBUTION, MANAGEMENT OR USAGE, i.e. SMART GRIDS
- Y04S40/00—Systems for electrical power generation, transmission, distribution or end-user application management characterised by the use of communication or information technologies, or communication or information technology specific aspects supporting them
Definitions
- the present invention relates to a computer-implemented method for determining the structure of an electricity distribution network, an associated computer program and a system for determining the structure of the electricity distribution network.
- the transformer station is, for example, a high-voltage / medium-voltage transformer station (HTB / HTA) or medium-voltage / low-voltage transformer (HTA / LV), and the electrical feeders are medium or low voltage feeders.
- HTB / HTA high-voltage / medium-voltage transformer station
- HTA / LV medium-voltage / low-voltage transformer
- the high voltage corresponds to a voltage higher than 50 kVolts (kV)
- the medium voltage corresponds to a voltage of between 1 kV and 50 kV
- the low voltage corresponds to a voltage of less than 1 kV.
- the consumers are powered either three-phase or single-phase, and the transformer station is configured to distribute the electrical power it receives between different electrical outputs.
- Electricity distributors therefore need to know more about the structure of electricity distribution networks, in particular to locate any faults or failures on the network or to identify the most significant losses from the transformer station in terms of losses. electric.
- EP 2 458 340 A2 a method for determining the structure of an electricity distribution network from specific calculation means and information relating to the electrical energy consumed by each electrical consumer connected to the network and relating to the electrical energy delivered by each departure from the transformer station.
- the object of the invention is therefore to provide a robust determination method of the structure of an electricity distribution network to determine the structure of the electricity distribution network in a safer, more reliable and faster.
- Such a method makes it possible to overcome any errors, for example related to inaccuracies in measuring the energy consumed and / or delivered or the absence of certain energy measurements.
- the steps of selecting the first set of data sets according to the first selection criteria calculated and determining the connection parameters from the first selected set allow to more reliably and quickly determine the structure of the electricity distribution system.
- the invention also relates to a computer program comprising software instructions, which when executed by a computer implement the method defined above.
- a power distribution network 10 is associated with a system 12 for determining the structure of the electricity distribution network 10.
- the distribution network 10 comprises a power supply station 14 for the electrical energy of several electrical consumers 16 i .
- the feed station 14 comprises electric feeders 18 j of electrical power supply of the electrical consumers 16 i , with i an electrical consumer index and a starting index.
- the index i of electrical consumer varies from 1 to n, where n is the number of electrical consumers 16 i and the starting index j varies from 1 to m, where m is the number of electrical starts 18 j .
- the number n of electrical consumers 16 i is equal to 3
- the number m of electrical outputs 18 j is equal to 2.
- the determination system 12 comprises, for each electrical consumer 16 i , a first energy measurement sensor 20 i and a transmission module 21 i of energy measurements made by the corresponding first sensor 20 i .
- the determination system 12 comprises, for each start 18 j , a second sensor 22 j energy measurement.
- the determination system 12 also comprises an information processing unit 24 formed for example of a processor 26 and a memory 28 associated with the processor 26.
- the feed station 14 is, for example, a medium voltage / low voltage transformer station connected between a medium voltage network, not shown, and a low voltage network 30 corresponding to the electrical consumers 16 i .
- the feed station 14 includes, at each start 18 j , the corresponding second sensor 22 j .
- the electrical consumers 16 i are connected to the power station 14 via the 18 j departures. More specifically, in the example of figure 1 the electrical consumers 16 1 , 16 2 are connected to the start 18 1 and the electrical consumer 16 3 is connected to the start 18 2 .
- the electrical consumers 16 i are either three-phase and powered by the corresponding start 18 j via four electrical conductors 32 d , 34 d , 36 d , 38 d , that is to say three electrical conductors 32 d , 34 d , 36 j and a neutral electrical conductor 38 j , either single-phase and powered by the corresponding junction 18 j via two electrical conductors: that is to say, for example a phase conductor 32 d , 34 d or 36 d and the neutral conductor 38 days
- the electrical consumer 16 1 is three-phase and the electrical consumers 16 2 , 16 3 are single-phase.
- Each electrical consumer 16 i includes one of the first corresponding sensors 20 i and one of the corresponding transmission modules 21 i .
- Each electrical consumer 16 i is, for example, a communicating power consumption counter, able to measure first data E Ci relating to the electrical energy consumed by the electrical consumer 16 i , via the corresponding first sensor 20 i , and to transmit the first data E Ci to the processing unit 24 via the corresponding transmission module 21 i .
- Each feeder 18 j is a three-phase feeder and comprises the three phase conductors 32 j , 34 j , 36 j corresponding and the corresponding neutral conductor 38 j .
- the electrical outputs are single-phase and comprise a phase conductor and a neutral conductor.
- some departures are single-phase and others are three-phase.
- Each first sensor 20 i is adapted to measure the first data E Ci (t l ) relative to the electrical energy consumed by the corresponding electrical consumer 16 i , during different time intervals t l .
- the first sensors 20 i are configured to measure the first data E Ci (t 1 ) during the same time intervals t 1 , the first data E Ci (t 1 ) measured at the level of each electrical consumer 16 i being measured from synchronously.
- Each transmission module 21 i is able to transmit the first data E ci (t l ) measured by the corresponding first sensor 20 i to the processing unit 24.
- each transmission module 21 i is able to transmit with the first data E Ci (t 1 ) a first piece of information relating to the time interval during which the first data has been measured.
- Each second sensor 22 j is able to measure second data E Dj (t l ) relative to the electrical energy delivered by the corresponding start 18 j during the different time intervals t l .
- the first E Ci (t 1 ) and second E d 1 (t 1 ) measured data are then synchronized in the sense that they are measured during identical time intervals t 1 .
- Each second sensor 22 j is also configured to transmit, via a respective electrical connection 40 j , the second data E Dj (t l ) that it measures to the processing unit 24.
- each second sensor 22 j is configured to transmit with the second data E Dj (t 1 ) a second piece of information relating to the time interval t 1 during which the second data E Dj (t 1 ) have been measured.
- the first E Ci (t 1 ) and second E Dj (t 1 ) data are, for example, active energy measurements.
- the first E Ci (t 1 ) and the second E d 1 (t 1 ) data are active energy measurements.
- the first E Ci (t 1 ) and the second E d 1 (t 1 ) data are reactive energy measurements, apparent energy measurements, active power measurements, reactive power measurements, apparent power or intensity measurements.
- the processor 26 is configured to execute software included in the memory 28.
- the memory 28 comprises a software 41 for acquiring the first E Ci (t 1 ) and second data E Dj (t 1 ) data, a software 42 for generating several different data sets I 1 from the first data E Ci (t 1). l ) and second data E Dj (t l ) acquired in the same time interval t l and software 44 for calculating a first selection criterion C1 l for each data set Je l .
- the memory 28 also comprises a software 46 for selecting a first set 1 of data sets Je 1 , as a function of the first selection criteria C1 1 calculated by the calculation software 44 and a software 48 for determining connection parameters. a ij , said connection parameters comprising for each electrical consumer 16 i an identifier of the start 18 j to which it is connected.
- the acquisition software 41, generation 42, calculation 44, selection 46 and determination 48 correspond to software instructions and form a computer program capable of being executed by a computer.
- the computer corresponds, for example, to the processing unit 24.
- the acquisition software 41 is clean, for example, to transmit to each electrical consumer 16 i and in particular to each first sensor 20 i an order of measuring the first data E Ci (t l ) and a transmission order of the first data E Ci (t l ), in order to recover the first data.
- the acquisition software 41 is, for example, configured to transmit to each start 18 j and in particular to each second sensor 22 j a measurement order of the second data E Dj (t l ) and a transmission order of the second data E Dj (t l ), in order to recover the second data E Dj (t l ).
- the measurement orders of the first E Ci (t 1 ) and second E Dj (t 1 ) data are transmitted simultaneously to all the departures 18 j and all the consumers 16 i .
- the generation software 42 is configured to generate the data sets Je 1 which are each associated with one of the time intervals t 1 and which comprise the first E Ci (t 1 ) and the second E d 1 (t 1 ) data associated with the said time interval t l .
- the generation software 42 selects the first E Ci (t 1 ) and the second E d 1 (t 1 ) data measured during the different time intervals t 1 , to create the data sets Je l .
- the calculation software 44 is adapted to calculate, for each data set Je I , the first selection criterion C1 1 , which is chosen from a global rate of electrical energy losses between the feeders 18 j and the electrical consumers 16 i and a difference in power consumption between the different consumers 16 i .
- the losses of electrical energy include both so-called technical losses, for example related to Joule losses during the flow of current between departures 18j and consumers 16i, the so-called non-technical losses, which are for example related to theft electricity, the fact that consumers are connected to the distribution network 10 without the information processing unit 24 being informed and first defective sensors 20 i .
- the first selection criterion C1 1 is, for example, the overall rate of electrical energy losses between the feeders 18 j and the consumers 16 i .
- the first selection criterion C1 1 is, for example, the relative difference in power consumption between the different consumers
- the selection software 46 is configured to select the first set In 1 of data sets among the data sets I l generated by the generation software 42, according to the first selection criteria C1 l calculated.
- the selection software 46 is, for example, configured to compare the first criteria C1 1 with a first predetermined variable V 1 and to select the data sets Je 1 for which the first criterion C1 1 is smaller than the first predetermined variable V 1.
- the determination software 48 is configured to determine the connection parameters a ij from the first set En 1 selected.
- the determination software 48 is, for example, configured to establish or determine an equation system to be solved from an electrical energy conservation postulate for each departure 18 j , according to which the energy delivered by the departure 18 j is substantially equal to the sum of the energy consumed by the electrical consumers 16 i initially connected 18 j and electrical losses.
- the optimization algorithm balances the energy deviations with the adjustment variables ⁇ 1 jk , ⁇ 2 jk so that the equalities of the equation system are verified.
- the energy delivered on a departure of index j is surplus, we increase the corresponding adjustment variable ⁇ 1 jk and if this energy is deficient, we increase the variable ⁇ 2 jk corresponding.
- the more the connection parameters ij respect the principle of energy conservation the more the adjustment variables are weak.
- the goal is to minimize the adjustment variables, which results in the objective function f T .
- connection parameters a ij are real numbers, which makes it possible to relax the constraints.
- the determination software 48 is configured to set the values of the connection parameters a ij to 0 or to 1 according to their value following the application of the optimization algorithm.
- the value 0 indicates a non-connection of the consumer of index i at the beginning of index j
- the value 1 indicates a connection of the consumer of index i at the beginning of index j.
- each consumer 16 i is connected to a single start 18 j.
- processing unit 24 is configured to identify, as a function of the determined connection parameters and from, for example, identification software, not shown, included in the memory 28, subsets of consumers, with each subset of consumers corresponding to all consumers 16 i connected to the same party 18 days,.
- the determination software 48 is configured to determine the connection parameters separately for each start and independently of the second electric power data acquired for the other starts.
- an optimal equation system is determined for each departure and the optimization algorithm is applied to each optimal equation system. This results in m optimal equation systems solved independently via the optimization algorithm.
- the determination software 48 is, for example, able to determine the values of the connection parameters via equation (7).
- the determination software 48 is configured to determine the connection parameters for each phase electrical conductor 32 j , 34 j , 36 j and not simply for each departure 18 j .
- the equation system then comprises much equation of electrical conductors of phase 32 j, 34 j, 36 j and the variables described above and relating to a specific starting j are then related to a driver specific phase.
- the second sensors 22 j measure the electrical energy delivered by each phase conductor 32 j , 34 j , 36 j and not each departure 18 j , the connection parameters a ij are determined for each phase conductor 32 j , 34 j, 36 j, and the adjusting variables are determined for each phase conductor 32 j, 34 j, 36 j.
- each electrical conductor is identified by an index and the variable j, presented in the equations above, then corresponds to an electrical phase conductor index and varying from 1 to u, with u the number of electrical conductors in phase which is equal to 3 * m, ie 6 in the example of the figure 1 .
- the method comprises an initial step 100 of main data acquisition of the distribution network 10.
- the main data includes, for example, the total number n of consumers 16 i, the total number of departures m 18 j, the first data E Ci ( t l ) measured, the second data E Dj (t l ) measured and the different time intervals t l associated with the first and second measured data.
- the acquisition software 41 controls, for example, the measurement, by each first 20 i and second 22 j sensors, first E Ci (t l ) and second E Dj ( t l ) data during the time intervals t l and the transmission of the first E Ci (t l ) and second E Dj ( t l ) data which are then associated with the time interval t l during which they were measured, via, for example, the first and second information.
- the generation software 42 generates several different data sets Je 1 , each associated with one of the time intervals t 1 and which comprise the first E Ci (t 1 ) and the second E Dj (t l ) data associated with said time interval t l .
- the calculation software 44 calculates the first selection criterion C1 1 for each data set Je l .
- the first selection criterion C1 l is, for example, the overall rate of electrical energy losses between the departures 18 j and the consumers 16 i .
- the selection software 46 selects the first set En 1 based on the first selection criteria C1 l calculated.
- the first set In 1 is selected from the data sets generated in step 102.
- the selection software 46 compares, for example, the first criteria C1 1 with the first predetermined variable V1 , the value of the first predetermined variable V1 being for example defined during the acquisition step 100.
- the selection software 46 selects the data sets Je l for which the first criterion C1 l is less than the first predetermined variable V1.
- connection parameters are determined via the determination software 48 and from the first set In 1 selected.
- the determination software 48 determines the equation system to be solved from, for example, equation (4), as discussed above. Then, as presented above in the description of the determination system 12 and the equation (5), the optimization algorithm is applied to the equation system to determine the connection parameters a ij .
- the determination software 48 determines the optimal equation systems, as presented above via equation (8), and applies the optimization algorithm to each system of determination. optimal equation. The speed of determination of the connection parameters a ij is then improved, since the optimal equation systems comprise a limited number of equations.
- connection parameters a ij the fact of making a selection of the data sets Je k makes it possible to eliminate the data sets Je l for which the losses are the most important, these datasets being liable to lead to an erroneous determination of the data sets.
- connection parameters determined a ij are determined more certain compared to known methods of the state of the art and the reliability of the determination method is improved.
- the optimization algorithm used makes it possible to use an indifferent number of data sets Je k during the determination step 108, even if it is preferable that the number of datasets of the first set is greater than or equal to the total number n of consumers 16 i .
- the method comprises steps 200, 202, 204, 206, 208 identical respectively to steps 100, 102, 104, 106, 108 of the first embodiment and, in step 204, a second selection criterion C2 1 is calculated for each dataset generated.
- the second selection criterion C2 l is different from the first criterion C1 l and is chosen from a global rate of electrical energy losses between the starter (s) and the consumers and a difference in consumption of electrical energy between the different consumers.
- each first criterion C1 1 is, for example, the overall loss rate relative to the corresponding data set Je l and each second criterion C2 l is the difference in electric energy consumption relative to the data set I l corresponding, and is calculated via equation (2) or equation (3).
- the selection software 46 selects the first set En 1 according to the first selection criteria C1 1 and the second selection criteria C2 l calculated.
- the first set In 1 is selected from the data sets generated in step 202.
- the selection software 46 compares, for example, the first criteria C1 1 with the first variable V 1 and the second criteria C2 l with a second predetermined variable V2.
- the value of the second predetermined variable V2 is, for example, defined during the acquisition step 200.
- the selection software 46 selects the data sets for which the first criterion C1 l is less than the first predetermined variable V1 and the second criterion C2 l is less than the second predetermined variable V2.
- connection parameters are determined via the determination software 48 and from the first set selected in 1 .
- the second embodiment makes it possible to refine the selection of the data sets with respect to the first embodiment and thus to select data sets from which the risk of error in the determination of the connection parameters a ij is minimized. The accuracy, speed and reliability of the determination method are thus improved.
- the method comprises steps 300, 302, 304, 306, 310 identical respectively to steps 100, 102, 104, 106, 108 of the first embodiment and, following step 306 and previously at step 310, the method comprises a step 307 of calculating a second selection criterion C2 k for each set of data of the first set En 1 , the second criterion C2 k being different from the first criterion and being chosen from a global rate of electrical energy losses between the departure (s) 18 i and the consumers 16 i and a difference in power consumption between the different consumers 16 i .
- each first criterion C1 1 is, for example, the overall loss rate relative to the corresponding data set generated in step 302 and each second criterion C2 k is the difference in electrical energy consumption. relating to the corresponding dataset of the first set In 1 .
- a second set En 2 of data sets is selected from the first set En 1 .
- the first set In 1 is, for example, set equal to the second set selected in 2 to perform the determination step 310 as a function of the second set selected in 2 .
- the third embodiment makes it possible to refine the selection of the data sets with respect to the first embodiment, and thus to select data sets from which the risk of error in the determination of the connection parameters at ij is minimized. .
- the accuracy, speed and reliability of the determination method are thus improved.
- the method comprises steps 400, 402, 404, 406 identical to steps 100, 102, 104, 106 of the first embodiment.
- the method comprises a step 408 for determining the connection parameters. More specifically, in step 408, the method comprises a first sub-step 408A of pseudo-random selection of a third set En 3 of data sets included in the first set En 1 .
- the repeat parameter R1 corresponds to a number of iterations of the selection sub-step 408A.
- intermediate indices b ij of connection indicating for each consumer 16 i the start 18 j to which it is connected, are determined from the third set selected in 3 . More generally, the intermediate indices b ij comprise for each electrical consumer 16 i a start identifier 18j to which it is connected.
- the determination sub-step 408C is analogous to the determination step 108 of the first embodiment, but is performed from the third set En 3 .
- the total number of iterations N T is initialized to 0 previously at the execution of the selection sub-step 408A and incremented by 1 at each execution of the selection sub-step.
- the number of intermediate connection indices memorized for a given electrical consumer 16 i and a given start 18 j is equal to the number of iterations of the selection sub-step 408A
- the calculated allocation numbers are stored following the calculation sub-step 408E.
- the repeat parameter R1 is compared with a predetermined repeat criterion CR1.
- the predetermined repeat criterion CR1 is, for example, initialized during the acquisition step 400.
- the repeat criterion CR1 is, for example, a minimum number of iterations of the selection sub-step 408A.
- the repeat parameter is less than the repeat criterion, then the selection steps 408A, calculation 408B, determination 408C, storage 408D, calculation 408E and comparison 408F are repeated. .
- a substep 408G for determining the connection parameters a ij is performed.
- connection parameters a ij are determined from or third sets selected in 3, and more precisely depending on the intermediate indices of connection b ij stored when storing substep 408D, and even more precisely according to the assignment numbers NA ij calculated at the last iteration of the sub-step 408E. More precisely, for each electrical consumer 16 i , the start index j corresponding to the largest assignment number NA ij is identified, and the connection parameter a ij corresponding to said consumer 16 i and said start 18 j is set equal at 1, the other connection parameters ij relative to said consumer being set equal to 0.
- a connection identification error for said consumer 16 i is identified.
- a first average of the numbers of allocation NA ij calculated at each iteration of the sub-step 408E, for each consumer 16 i and for each departure 18 j , is calculated.
- a second average of the assignment numbers NA ij calculated at the last iteration, for each consumer 16 i and for each departure 18 j , is calculated.
- a difference between the first average and the second average is calculated.
- the first and second averages are, for example, arithmetic, geometric or quadratic means ...
- the absolute value of the last difference calculated is compared with a second predetermined threshold S2, for example equal to 0.1. Then, if during the comparison sub-step 408F, the repeat parameter R1 is greater than the repeat criterion CR1 and the absolute value of the last calculated difference is smaller than the second threshold S2, then the sub-step 408G is performed. Otherwise, steps 408A, 408B, 408C, 408D, 408E and 408F are repeated.
- the fourth embodiment makes it possible, especially when the number of iterations of the sub-step 408A is greater than 2, to determine the connection parameters a ij from third sets En 3 of different data sets. Thus, the accuracy and reliability of the determination method are improved.
- the fourth embodiment advantageously makes it possible to identify each consumer 16 i for which the associated departure 18j is determined with a good confidence index and each consumer 16 i for which the associated departure 18j is indeterminate or determined with a bad index. of confidence. Indeed, as presented above, if during the determination sub-step 408G all the assignment numbers relating to a consumer 16 i are lower than the first predetermined threshold S1, for example equal to 0.6, then an error identification of the connection for said consumer 16 i is identified and the start 18j to which is connected the consumer 16 i is indeterminate.
- a number of allocation relative to a consumer 16 i is greater than a third predetermined threshold S3, for example equal to 0.95, then the connection of the consumer 16 i initially 18j corresponding is identified with a good confidence index.
- the fourth embodiment makes it possible to associate, at each connection parameter a ij , set equal to 1 during the determination sub-step 408G, a confidence index representing the probability that the determined connection is correct.
- the confidence index is for example equal to the corresponding assignment number NA ij .
- the second embodiment is adapted to be combined with the fourth embodiment and the third embodiment is also adapted to be combined with the fourth embodiment.
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Applications Claiming Priority (1)
Application Number | Priority Date | Filing Date | Title |
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FR1553646A FR3035496B1 (fr) | 2015-04-23 | 2015-04-23 | Procede et systeme de determination de la structure d'un reseau de distribution d'electricite et programme d'ordinateur associe |
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EP3086093A1 true EP3086093A1 (de) | 2016-10-26 |
EP3086093B1 EP3086093B1 (de) | 2017-09-20 |
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EP16166742.3A Active EP3086093B1 (de) | 2015-04-23 | 2016-04-22 | Verfahren und system zur bestimmung der struktur eines stromverteilungsnetzes, und entsprechendes computerprogramm |
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US (1) | US10431979B2 (de) |
EP (1) | EP3086093B1 (de) |
AU (1) | AU2016202536B2 (de) |
ES (1) | ES2651481T3 (de) |
FR (1) | FR3035496B1 (de) |
Cited By (1)
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WO2019053588A1 (en) | 2017-09-12 | 2019-03-21 | Depsys Sa | METHOD OF ESTIMATING THE TOPOLOGY OF AN ELECTRICAL NETWORK USING MEASUREMENT DATA |
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EP3502627B1 (de) * | 2017-12-21 | 2020-09-23 | Fundacíon Tecnalia Research & Innovation | Zuweisung und verbindung von elektrizitätskunden mit phasen einer verteilungseinspeisung |
CN110729724A (zh) * | 2019-10-25 | 2020-01-24 | 山东电工电气集团有限公司 | 一种低压配电台区拓扑自动识别方法 |
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WO2009061291A1 (en) * | 2007-11-05 | 2009-05-14 | Square D Company | Improvements in hierarchy determination for power monitoring systems |
US20110184576A1 (en) * | 2010-01-28 | 2011-07-28 | Schneider Electric USA, Inc. | Robust automated hierarchical determination for power monitoring systems |
EP2458340A2 (de) | 2010-11-25 | 2012-05-30 | Schneider Electric Industries SAS | Verfahren und Vorrichtung zur Bestimmung der Struktur eines Stromverteilungsnetzes |
WO2012113936A1 (en) * | 2011-02-24 | 2012-08-30 | Eandis | Method for detecting low voltage connectivity in part of an electricity grid |
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WO2019053588A1 (en) | 2017-09-12 | 2019-03-21 | Depsys Sa | METHOD OF ESTIMATING THE TOPOLOGY OF AN ELECTRICAL NETWORK USING MEASUREMENT DATA |
US11205901B2 (en) | 2017-09-12 | 2021-12-21 | Depsys Sa | Method for estimating the topology of an electric power network using metering data |
Also Published As
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AU2016202536B2 (en) | 2019-09-26 |
FR3035496B1 (fr) | 2017-05-26 |
FR3035496A1 (fr) | 2016-10-28 |
EP3086093B1 (de) | 2017-09-20 |
AU2016202536A1 (en) | 2016-11-10 |
US20160315469A1 (en) | 2016-10-27 |
ES2651481T3 (es) | 2018-01-26 |
US10431979B2 (en) | 2019-10-01 |
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